Quantitative perfusion assessment using indocyanine green during surgery — current applications and recommendations for future use

吲哚青绿 灌注 荧光寿命成像显微镜 生物医学工程 软件 灌注扫描 医学 计算机科学 荧光 医学物理学 放射科 病理 量子力学 物理 程序设计语言
作者
Pim van den Hoven,Jens Osterkamp,Nikolaj Nerup,Morten Bo Søndergaard Svendsen,Alexander L. Vahrmeijer,Joost R. van der Vorst,Michael Patrick Achiam
出处
期刊:Langenbeck's Archives of Surgery [Springer Nature]
卷期号:408 (1) 被引量:13
标识
DOI:10.1007/s00423-023-02780-0
摘要

Abstract Purpose Incorrect assessment of tissue perfusion carries a significant risk of complications in surgery. The use of near-infrared (NIR) fluorescence imaging with Indocyanine Green (ICG) presents a possible solution. However, only through quantification of the fluorescence signal can an objective and reproducible evaluation of tissue perfusion be obtained. This narrative review aims to provide an overview of the available quantification methods for perfusion assessment using ICG NIR fluorescence imaging and to present an overview of current clinically utilized software implementations. Methods PubMed was searched for clinical studies on the quantification of ICG NIR fluorescence imaging to assess tissue perfusion. Data on the utilized camera systems and performed methods of quantification were collected. Results Eleven software programs for quantifying tissue perfusion using ICG NIR fluorescence imaging were identified. Five of the 11 programs have been described in three or more clinical studies, including Flow® 800, ROIs Software, IC Calc, SPY-Q™, and the Quest Research Framework®. In addition, applying normalization to fluorescence intensity analysis was described for two software programs. Conclusion Several systems or software solutions provide a quantification of ICG fluorescence; however, intraoperative applications are scarce and quantification methods vary abundantly. In the widespread search for reliable quantification of perfusion with ICG NIR fluorescence imaging, standardization of quantification methods and data acquisition is essential.
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